Linking 2,000 years of Sedimentation in the Western

Arctic Ocean to an Atmospheric Temperature Proxy Record from a Glacial Lake in the Brooks Range,

Alaska

Jeffrey M HarrisonDepartment of GeologyKent State University

jharri72@kent.edu

HARRISON, Jeffrey M, ORTIZ, Joseph D, ABBOTT, Mark B, BIRD, Broxton W, HACKER, David B, GRIFFITH, Elizabeth M, and DARBY, Dennis A

Previous Research Work conducted by:Darby, D. A., J. D. Ortiz, L. Polyak, S. P. Lund, M. Jakobsson, and R. A. Woodgate (2009). The role of currents and sea ice in both slowly deposited central Arctic and rapidly deposited Chukchi-Alaskan margin sediments. Global and Planetary Change, 68: 58-72.

Analyzed the grain-size distribution of a marine core (JPC-16) Compared core sediment to sea-ice entrained sediments

Looked at the entire Holocene (~8,000 years)

This research enhances the resolution of the Marine Core Same analytical methods 18 & 35 yr sample interval vs. ~88 yr interval

Looked at the recent Holocene (Last 2,000 years)

Purpose of Study

Characterize marine sedimentation at a higher resolution

Identify how atmospheric climate is related to patterns of sedimentation in the western Arctic Basin

Aid in a better understanding of the distribution and circulation of sea-ice related to atmospheric patterns Data reflects natural variability

WesternArctic

EasternArctic

Marine CoreDrag picture to placeholder or click icon to add

• This study examines marine sedimentation processes on the Alaskan Continental shelf

• Samples analyzed for grain-size distributions

• Performed statistical analysis to determine mechanisms that contribute to the majority of the variation in the core section

• The core site is influenced by:

• Ocean Currents• Eddies that spinoff as water moves

down the central-axis of Barrow Canyon

• An Annual sea-ice cover• Storm events and reworking of

sediments

Sea-Ice Sea-ice in the Arctic

has been decreasing dramatically since the 1970’s

Fluctuations in sea-ice have occurred throughout geologic history

How is sea-ice connected to atmospheric variability?

Malvern Analysis Analysis of diffracted

light produced when a laser beam passes through dispersed particles

Particularly useful for measuring very fine grained particles

Particle size distributions are calculated by comparing a sample’s scattering pattern with an appropriate optical model

Laser Diffraction Method

Mie Scattering TheoryLarger particles diffract light at greater angles and therefore, the light from these is detected by sensors closer to the window.

Counts from the sensors are tallied, averaged and reported as a grain-size distribution.

From Malvern

Malvern ResultsBin Number particle size

(um)

Bin024 0.30Bin025 0.34Bin026 0.38Bin027 0.42Bin028 0.48Bin029 0.53Bin030 0.60Bin031 0.67Bin032 0.75Bin033 0.84Bin034 0.95Bin035 1.06Bin036 1.19Bin037 1.34Bin038 1.50Bin039 1.69Bin040 1.89Bin041 2.12Bin042 2.38Bin043 2.67Bin044 3.00Bin045 3.36Bin046 3.77Bin047 4.23Bin048 4.75Bin049 5.33Bin050 5.98Bin051 6.71Bin052 7.53Bin053 8.45Bin054 9.48Bin055 10.64Bin056 11.93Bin057 13.39Bin058 15.02Bin059 16.86Bin060 18.91Bin061 21.22Bin062 23.81Bin063 26.71Bin064 29.97Bin065 33.63Bin066 37.74Bin067 42.34Bin068 47.51Bin069 53.30Bin070 59.81

Shows how overall mean grain-size varies through

time

Principal Component Analysis (PCA)

Used to discover or reduce the dimensionality of a data set For data of high dimensions, where graphical

representation is difficult, PCA is a powerful tool for analyzing data and finding patterns within a dataset (grouping).

Identifies meaningful and underlying variations Grain-size bins produced by the Malvern are placed

in to different groups Each component explains some underlying variance

within the data

PCA Components

Anchor IceSuspensionFreezing

WinnowedSilt

JPC-16 Components

Marine Record

The three significant modes of sedimentation can be described as:a) Component 1: Anchor Iceb) Component 2: Nepheloid Flows or winnowed siltc) Component 3: Suspension Freezing

Components through Time

0.62 Correlation b/w PC-1 & PC-3

PC-2 likely represent more of a marine

influence

Blue Lake Within the crest of

the Brooks Range Retrieved cores

show millimeter scale laminations

Glacially fed

From Bird et al., 2009

Bird, B. W., M. B. Abbott, B. P. Finney, and B. Kutchko (2009). A 2000 year varve-based climate record from the central Brooks Range, Alaska. Journal of Paleolimnology, 41: 25-41.

Varve Formation

An annually resolved record Indicate variations in

summer melt characteristics

Varve couplet reflects seasonal sedimentation

Light (reddish), coarser

material results from sedimentation during periods of meltwater discharge

Dark, finer layers form when fine-organic particles settle out due to stagnant conditions (ice covered)

From Bird et al., 2009

Blue Lake Temperature

From Bird et al., 2009

The thicker varves are related to warmer temperatures and an increase in precipitation

Record CorrelationZero lag Correlation = 0.74 (p<0.01)Max Lag = 0.75 (-1)

Zero lag Correlation = 0.41 (p<0.05)Max Lag = 0.53 (1)

Arctic Oscillation (AO)

The AO is the dominant mode in atmosphere circulation and sea ice drift variability (Decadal)

Positive and Negative phases affect drift in the Arctic Positive Phase: low pressure system dominates the

Arctic and causes storms to move northward Negative Phase: High pressure system that causes cold out burst to the temperate regions

AOTwo Dominant Regimes

• Colder winter temperatures• Strong Beaufort Gyre

• Warmer winter temperatures• Transpolar Drift Stream

sweeps ice out of Arctic Ocean

Negative AO Positive AO

ICETransport Towards

Alaska

From Darby et al., 2012

Conclusions

Release of sediment from sea-ice imparts a unique textural signature on the marine deposits

Western Arctic sea-ice transport/sedimentation is significantly correlated to Northern Alaskan atmospheric climate (temp. proxy) It is likely that shifts in pressure systems in the Arctic affect

both sea-ice and terrestrial climate Changes in the phase of the AO would explain:

The influx of sea-ice-related sediment towards the Alaskan shelf (JPC-16)

The increase in varve thickness found in Blue Lake prior to 1,200 yr BP

Thank You !!!

Questions

References Bird, B. W., M. B. Abbott, B. P. Finney, and B. Kutchko (2009). A 2000 year varve-

based climate record from the central Brooks Range, Alaska. Journal of Paleolimnology, 41: 25-41.

Darby, D. A., J. D. Ortiz, C. E. Grosch, and S. P. Lund (2012). 1,500-year cycle in the Arctic Oscillation identified in Holocene Arctic sea-ice drift. Nature Geoscience, 5: 897-900.

Darby, D. A., J. D. Ortiz, L. Polyak, S. P. Lund, M. Jakobsson, and R. A. Woodgate (2009). The role of currents and sea ice in both slowly deposited central Arctic and rapidly deposited Chukchi-Alaskan margin sediments. Global and Planetary Change, 68: 58-72.

Jakobsson, M., L. A. Mayer, B. Coakley, J. A. Dowdeswell, S. Forbes, B. Fridman, H. Hodnesdal, R. Noormets, R. Pedersen, M. Rebesco, H. W. Schenke, Y. Zarayskaya A, D. Accettella, A. Armstrong, R. M. Anderson, P. Bienhoff, A. Camerlenghi, I. Church, M. Edwards, J. V. Gardner, J. K. Hall, B. Hell, O. B. Hestvik, Y. Kristoffersen, C. Marcussen, R. Mohammad, D. Mosher, S. V. Nghiem, M. T. Pedrosa, P. G. Travaglini, and P. Weatherall (2012). The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0. Geophysical Research Letters, 39: L12609.

Malvern-Instruments (1997). Manual: Mastersizer S & X, Getting Started, Issue 1.3. Malvern Instruments Ltd., Malvern, UK, pp. 98.

Combined Sea-Ice Components

From Darby et al., 2012

Age-Depth Model

Blue Lake Vs Burial Lake